library(poppr)
data(Pinf)
tab <- mlg.table(Pinf, plot = FALSE)
diversity_stats(tab)
## Not run:
# # Example using the poweRlaw package to calculate the negative slope of the
# # Pareto distribution.
#
# library("poweRlaw")
# power_law_beta <- function(x){
# xpow <- displ(x[x > 0]) # Generate the distribution
# xpow$setPars(estimate_pars(xpow)) # Estimate the parameters
# xdat <- plot(xpow, draw = FALSE) # Extract the data
# xlm <- lm(log(y) ~ log(x), data = xdat) # Run log-log linear model for slope
# return(-coef(xlm)[2])
# }
#
# Beta <- function(x){
# x <- drop(as.matrix(x))
# if (length(dim(x)) > 1){
# res <- apply(x, 1, power_law_beta)
# } else {
# res <- power_law_beta(x)
# }
# return(res)
# }
#
# diversity_stats(tab, B = Beta)
# ## End(Not run)
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